Detecting rare functional variants using a wavelet-based test on quantitative and qualitative traits

نویسندگان

  • Renfang Jiang
  • Jianping Dong
چکیده

We conducted a genome-wide association study on the Genetic Analysis Workshop 17 simulated unrelated individuals data using a multilocus score test based on wavelet transformation that we proposed recently. Wavelet transformation is an advanced smoothing technique, whereas the currently popular collapsing methods are the simplest way to smooth multilocus genotypes. The wavelet-based test suppresses noise from the data more effectively, which results in lower type I error rates. We chose a level-dependent threshold for the wavelet-based test to suppress the optimal amount of noise according to the data. We propose several remedies to reduce the inflated type I error rate: using a window of fixed size rather than a gene; using the Bonferroni correction rather than comparing to the maxima of test values for multiple testing corrections; and removing the influence of other factors by using residuals for the association test. A wavelet-based test can detect multiple rare functional variants. Type I error rates can be controlled using the wavelet-based test combined with the mentioned remedies.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Methods for adjusting population structure and familial relatedness in association test for collective effect of multiple rare variants on quantitative traits

Because of the low frequency of rare genetic variants in observed data, the statistical power of detecting their associations with target traits is usually low. The collapsing test of collective effect of multiple rare variants is an important and useful strategy to increase the power; in addition, family data may be enriched with causal rare variants and therefore provide extra power. However,...

متن کامل

Utilizing mutual information for detecting rare and common variants associated with a categorical trait

Background. Genome-wide association studies have succeeded in detecting novel common variants which associate with complex diseases. As a result of the fast changes in next generation sequencing technology, a large number of sequencing data are generated, which offers great opportunities to identify rare variants that could explain a larger proportion of missing heritability. Many effective and...

متن کامل

An aggregating U-Test for a genetic association study of quantitative traits

We propose a novel aggregating U-test for gene-based association analysis. The method considers both rare and common variants. It adaptively searches for potential disease-susceptibility rare variants and collapses them into a single "supervariant." A forward U-test is then used to assess the joint association of the supervariant and other common variants with quantitative traits. Using 200 sim...

متن کامل

Power of selective genotyping in genome-wide association studies of quantitative traits

The selective genotyping approach in quantitative genetics means genotyping only individuals with extreme phenotypes. This approach is considered an efficient way to perform gene mapping, and can be applied in both linkage and association studies. Selective genotyping in association mapping of quantitative trait loci was proposed to increase the power of detecting rare alleles of large effect. ...

متن کامل

A goodness-of-fit association test for whole genome sequencing data

Although many genetic factors have been successfully identified for human diseases in genome-wide association studies, genes discovered to date only account for a small proportion of overall genetic contributions to many complex traits. Association studies have difficulty in detecting the remaining true genetic variants that are either common variants with weak allelic effects, or rare variants...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 5  شماره 

صفحات  -

تاریخ انتشار 2011